Gene Louis Kim

Orcid: 0000-0002-3375-1957

Affiliations:
  • University of South Florida, Bellini College of Artificial Intelligence, Cybersecurity and Computing, Tampa, FL, USA
  • University of South Florida, Department of Computer Science and Engineering, Tampa, FL, USA
  • University of Rochester, Department of Computer Science, Rochester, NY, USA (PhD 2022)
  • University of Washington, Seattle, WA, USA (former)


According to our database1, Gene Louis Kim authored at least 23 papers between 2014 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Event Detection with a Context-Aware Encoder and LoRA for Improved Performance on Long-Tailed Classes.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2026, 2026

2025
Breaking the Benchmark: Revealing LLM Bias via Minimal Contextual Augmentation.
CoRR, October, 2025

Prompting Techniques for Reducing Social Bias in LLMs through System 1 and System 2 Cognitive Processes.
Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing, 2025

From Anger to Joy: How Nationality Personas Shape Emotion Attribution in Large Language Models.
Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2025

Evaluating the Impact of Racial Cues on MLLMs Judgements of Politeness and Offensiveness.
Proceedings of the IEEE/CVF International Conference on Computer Vision, ICCV 2025, 2025

The Impact of Disability Disclosure on Fairness and Bias in LLM-Driven Candidate Selection.
Proceedings of the 38th International Florida Artificial Intelligence Research Society Conference, 2025

Exploring Changes in Nation Perception with Nationality-Assigned Personas in LLMs.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

BanStereoSet: A Dataset to Measure Stereotypical Social Biases in LLMs for Bangla.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

The Impact of Name Age Perception on Job Recommendations in LLMs.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024
Monotonic Inference with Unscoped Episodic Logical Forms: From Principles to System.
J. Log. Lang. Inf., March, 2024

"A Woman is More Culturally Knowledgeable than A Man?": The Effect of Personas on Cultural Norm Interpretation in LLMs.
CoRR, 2024

"Global is Good, Local is Bad?": Understanding Brand Bias in LLMs.
CoRR, 2024

"Global is Good, Local is Bad?": Understanding Brand Bias in LLMs.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Investigating Subtler Biases in LLMs: Ageism, Beauty, Institutional, and Nationality Bias in Generative Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

Finetuning LLMs for Automatic Concept to TTI Prompt Generation (Student Abstract).
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
BanMANI: A Dataset to Identify Manipulated Social Media News in Bangla.
CoRR, 2023

Efficient Sentiment Analysis: A Resource-Aware Evaluation of Feature Extraction Techniques, Ensembling, and Deep Learning Models.
CoRR, 2023

2021
A Transition-based Parser for Unscoped Episodic Logical Forms.
CoRR, 2021

2020
Montague Grammar Induction.
CoRR, 2020

2019
A Type-coherent, Expressive Representation as an Initial Step to Language Understanding.
Proceedings of the 13th International Conference on Computational Semantics, 2019

2016
High-Fidelity Lexical Axiom Construction from Verb Glosses.
Proceedings of the Fifth Joint Conference on Lexical and Computational Semantics, 2016

2014
A format string checker for Java.
Proceedings of the International Symposium on Software Testing and Analysis, 2014

A type system for format strings.
Proceedings of the International Symposium on Software Testing and Analysis, 2014


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